Bayesian Adaptive Randomization Design

The Bayesian adaptive randomization design is an extension of adaptive research designs, which modify the randomization ratio during a study in order to maximize individual participant outcomes. Bayesian adaptive randomization designs use Bayesian data analysis to estimate the probability that each intervention maximizes the outcome of interest, and the randomization ratio is adjusted according to these estimates. In adjusting the randomization ratio based on which intervention is estimated to produce the most favorable outcome, Bayesian adaptive randomization designs maximize the likelihood of participants experiencing positive outcomes and minimize the likelihood of participants experiencing poor outcomes.

Bayesian adaptive randomization designs follow a four-step procedure. In Step 1, participants are randomly allocated to one of the interventions with the probability of allocation into each intervention being specified by ...

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